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Generative AI – The End of Empty Textboxes

TechEmpower Innovation

On a different project, we’d just used a Large Language Model (LLM) - in this case OpenAI’s GPT - to provide users with pre-filled text boxes, with content based on choices they’d previously made. This gives Mark more control over the process, without requiring him to write much, and gives the LLM more to work with.

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Innovation on Steroids: Next Generation AI-Powered Phases and Gates

Leapfrogging

AI technologies bring a new dimension of analytical capabilities and insights that were previously unattainable. By harnessing the power of AI, organizations are able to process vast amounts of data, identify patterns, and make more informed decisions at every phase of the innovation process.

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Embracing the Future: Fractional Executives and Generative AI

Tullio Siragusa

Embracing the Future: Fractional Executives and Generative AI The concept of fractional executives has emerged as a game-changer for companies of all sizes. The rise of Generative Artificial Intelligence (AI) has further empowered fractional executives, enabling them to produce full-time results in significantly less time.

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How Generative AI Will Transform Knowledge Work

Harvard Business Review

Generative AI can be a boon for knowledge work, but only if you use it in the right way. New generative AI-enabled tools are rapidly emerging to assist and transform knowledge work in industries ranging from education and finance to law and medicine. However, there is no need to wait for these externally-imposed changes.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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Managing the Risks of Generative AI

Harvard Business Review

Generative artificial intelligence (AI) has become widely popular, but its adoption by businesses comes with a degree of ethical risk. Organizations must prioritize the responsible use of generative AI by ensuring it is accurate, safe, honest, empowering, and sustainable.

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Is Your Company’s Data Ready for Generative AI?

Harvard Business Review

While CDOs and data leaders are excited about generative AI, they have much work to do to get ready for it. Despite excitement, companies have yet to see clear value from generative AI and need to do significant work to prepare their data.

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Building User-Centric and Responsible Generative AI Products

Speaker: Shyvee Shi - Product Lead and Learning Instructor at LinkedIn

In the rapidly evolving landscape of artificial intelligence, Generative AI products stand at the cutting edge. This presentation unveils a comprehensive 7-step framework designed to navigate the complexities of developing, launching, and scaling Generative AI products.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.